Abstract

Drools is the leading open source, industry focused, rule engine. While Drools started life as a Rete based forward chaining engine, it has since transcended. It's ongoing mission is to explore declarative paradigms from a practical and industrial perspective, to boldly go where no engine has gone before.

The tutorial will start with a gentle introduction, suitable for all level of expertise, covering the core language and functionality slowly expanding into more complex areas. The topics covered include, but are not limited to:

Basic Concepts:

• Patterns, Constraints and Unification
• Data Driven and Goal Oriented Inference using Forward Chaining and (Opportunistic) Backward Chaining
• Truth Maintenance
• Temporal Reasoning and Complex Event Processing
• Functional Programming
• Traits and Declarative Models

• Decision Tables
• Rule and Workflow Integration
• Hybrid Rule-Based Systems
• Agents and Services
• Unified Testing

Brief biography of Mark Proctor

Mark Proctor received his B.Eng in Engineer Science and Technology and then his M.Sc. in Business and Information Systems; both from Brunel University, West London. His M.Sc. thesis was in the field of Genetic Algorithms; which is where he discovered his interest for anything AI related.

Mark became involved in the Drools expert system project at an early stage and soon became its project lead. Mark then joined JBoss (later acquired by Red Hat) as an employee when the Drools project was federated into the JBoss middleware stack.
Mark now leads the effort at Red Hat for a unified platform for declarative technologies; with a focus on rules, event processing, workflow, semantics, distributed agents and governance.

Brief biography of Davide Sottara

Davide Sottara received his Ms. Degree in Computer Science(2006) and his Ph.D (2010) in Computer Science, Electronics and Telecommunications from the University of Bologna.
His research and development interests include Artificial Intelligence in general and Decision Support Systems in particular, focusing on hybrid systems combining predictive models and rule-based systems.

Since 2006, he has been working on the development of intelligent DSSs in the environmental and medical field. He is a member of the Drools open source Community, leading a sub-project on the extension of production rule engines to support hybrid and uncertain reasoning, and he's also involved in the RuleML rule language standardization initiative. He is currently working on remote health-care systems enhanced with AI-based predictive, diagnostic and planning features.